Abstract
Geophysical logging series are valuable geological data that record the physical and chemical information of borehole walls and in-situ formations, and are widely used by geologists for interpreting geological problems due to their continuity, high resolution, and ease of access. Recently, machine learning methods are gradually bringing data science and geoscience closer together, and Intelligent Recognition using Logging Data (IRLD) is increasingly becoming an important interpretation task. However, due to the specificity of geological information, relatively low data quality makes the direct application of machine learning models to IRLD often not optimal. And to the best of our knowledge, IRLDs are not highly generalizable and technical surveys are still lacking. Therefore, this paper presents a comprehensive review of IRLD. Specifically, after systematically reviewing geophysical well logging and machine learning techniques, the main applications and general processes for the cross-discipline task of IRLD are summarized. More importantly, the key challenges of IRLD in the four stages of data acquisition, feature engineering, model building, and practical application are discussed in this review. The potential risks of these challenges are visualized by using real logging data from a study area in the South China Sea and the example of a lithology identification task. For these challenges, we give the current state-of-the-art methods and feasible strategies in conjunction with published research. This comprehensive review is expected to provide insights for practitioners to construct more robust models and achieve more effective application results in IRLD.
SummaryUltra-low velocity zones (ULVZs) have been identified as regions of extremely low velocity anomalies in the Earth's lowermost mantle using seismic observations from reflected, refracted, and diffracted arrivals along the mantle side of the core-mantle boundary (CMB). Estimation of ULVZ geometrical (i.e., shape and size) and elastic (i.e., velocity and density) parameters with uncertainties is crucial in understanding the role of ULVZs in the ongoing dynamic processes within the Earth's mantle; however, these parameters are still poorly known due to uncertainties and tradeoffs of the seismically resolved ULVZ geometries and elastic parameters. Computation of synthetic waveforms for 2-D and 3-D ULVZs shapes is currently computationally feasible, but past studies utilize higher dimensional waveform modeling of mostly only low-frequency diffracted waves. Most studies focusing on high-frequency core-reflected waveforms (e.g., ScP) still use 1-D modeling approaches to determine ULVZ properties. This approach might lead to wrong results if the imaged structures have inherently 3-D geometries. This study investigates high-frequency synthetic ScP waveforms for various 2.5-D ULVZ geometries showing that additional seismic arrivals are generated even when the ScP geometrical ray path does not directly strike the location of the ULVZ. The largest amplitude additional phases in the 2.5-D models are post-cursor arrivals that are generated at the edges of the finite-length ULVZs. These newly identified ScP post-cursors can arrive within the ScsP post-cursor time window traditionally analyzed in 1-D ULVZ studies. These post-cursors might then be misidentified or constructively/destructively interfere with the ScsP postcursor, leading to incorrect estimation of ULVZ parameters. In this study we investigate the bias introduced by the 2.5-D morphologies on the 1D estimated ULVZ elastic properties in a Bayesian waveform inversion scheme. We further expand the Bayesian method by including the data noise covariance matrix in the inversion and compare it to an autoregressive noise model that was utilized in previous studies. From the application to the observed ScP data, we find that the new approach converges faster, particularly for the inversion of data from multiple events, and the new algorithm retrieves ULVZ parameters with more realistic uncertainties. The inversion of 2.5-D synthetic ScP waveforms suggests that the retrieved ULVZ parameters can be misleading with unrealistically high confidence if we do not consider the data noise covariance matrix in the inversion. Our new approach can also retrieve the shape of a multi-dimensional Gaussian ULVZ if its length is 12o or longer in the great circle arc direction. However, 2.5-D synthetic waveforms show additional waveform complexity which can constructively interfere with the ScP wavefield. Hence, in many cases the estimation of ULVZ properties using 1-D forward modeling can provide incorrect ULVZ parameters. Hence previous ULVZ modeling efforts using 1-D parameter estimation methods may be incorrect.
Unprecedented wildfires in Canada and parts of Amazonia last year were at least three times more likely due to climate change and contributed to high levels of CO2 emissions from burning globally, according to the first edition of a new systematic annual review.
The oxygen fugacity (fO2) of the mantle controls the speciation and mobility of volatiles within it, influencing the composition of volatiles released during mantle-derived magmatic activity, and thereby regulating the composition of the atmosphere.
Earthquake insurance in Iran: solvency of local insurers in light of current market practices
Mohsen Ghafory-Ashtiany and Hooman Motamed
Nat. Hazards Earth Syst. Sci., 24, 2707–2726, https://doi.org/10.5194/nhess-24-2707-2024, 2024
Iranian insurers have been offering earthquake coverage since the 1990s. However, despite international best practices, they still do not use modern methods for risk pricing and management. As such, they seem to be accumulating seismic risk over time. This paper examines the viability of this market in Iran by comparing the local market practices with international best practices in earthquake risk pricing (catastrophe modeling) and insurance risk management (European Solvency II regime).
Shaping shallow landslide susceptibility as a function of rainfall events
Micol Fumagalli, Alberto Previati, Paolo Frattini, and Giovanni B. Crosta
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-140,2024
Preprint under review for NHESS (discussion: open, 0 comments)
Shallow landslides are mass movements of limited thickness, mainly triggered by extreme rainfalls, that can pose a serious risk to the population. This study uses statistical methods to analyse and simulate the relationship between shallow landslides and rainfalls, showing that in the studied area shallow landslides are modulated by rainfall but controlled by lithology. A new classification method considering the costs associated with a misclassification of the susceptibility is also proposed.
The National Oceanic and Atmospheric Administration predicts the 2024 Atlantic hurricane season will be more active than normal. This comes after an energetic 2023 season, which brought the fourth-most named storms since 1950.
An optimal transformation method applied to diagnose the ocean carbon budget
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, 2024
The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Improving the Gaussianity of radar reflectivity departures between observations and simulations using symmetric rain rates
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024, 2024
A symmetric error model built by symmetric rain rates handles the non-Gaussian error structure of the reflectivity error. The accuracy and linearization of rain rates can further improve the Gaussianity.
A nitrate ion chemical-ionization atmospheric-pressure-interface time-of-flight mass spectrometer (NO3− ToFCIMS) sensitivity study
Stéphanie Alage, Vincent Michoud, Sergio Harb, Bénédicte Picquet-Varrault, Manuela Cirtog, Avinash Kumar, Matti Rissanen, and Christopher Cantrell
Atmos. Meas. Tech., 17, 4709–4724, https://doi.org/10.5194/amt-17-4709-2024, 2024
Calibration exercises are essential for determining the accuracy of instruments. We performed calibrations on a NO3¯ ToFCIMS instrument to determine its sensitivity and linearity for detecting various organic compounds. Our findings revealed significant variability, over several orders of magnitude, in the calibration factors obtained. The results suggest that relying on a single calibration factor from H2SO4 for the quantification of all compounds detected by this technique is not appropriate.
On the temperature stability requirements of free-running Nd:YAG lasers for atmospheric temperature profiling through the rotational Raman technique
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024, 2024
We study how the spectral characteristics of a solid-state laser in an atmospheric temperature profiling lidar using the Raman technique impact the temperature retrieval accuracy. We find that the spectral widening, with respect to a seeded laser, has virtually no impact, while crystal-rod temperature variations in the laser must be kept within a range of 1 K for the uncertainty in the atmospheric temperature below 1 K. The study is carried out through spectroscopy simulations.
Abstract
This paper addresses one of the critical questions of scientific inquiry: How do we know when a given data set is representative of the phenomenon being examined? For paleomagnetists, the question is often whether a particular data set sufficiently averaged paleosecular variation (PSV). To this aim, we updated an existing PSV data set that now comprises 2,441 site mean directions from 94 individual studies (PSV10-24). Minimal filtering for data quality resulted in 1,619 sites from 90 publications. Fitting PSV10-24 with two newly defined parameters as well as two existing ones form the basis of a Giant Gaussian Process field model (THG24) consistent with the data. Drawing directions from THG24 yields directional distributions predicted for a given latitude allowing a comparison between empirical distributions and the cumulative distribution function generated by the model. This tests whether the observed data adequately averaged out PSV according to THG24. We applied these tests to five data sets from Large Igneous Provinces from the last billion years and find that they are consistent with the THG24 model as well. Sedimentary data sets that may have experienced inclination shallowing can be corrected using an (un)flattening factor that yields directions satisfying THG24 in a newly-defined, four-parameter space. This approach builds on the Elongation-Inclination (E/I) method of Tauxe and Kent (2004), https://doi.org/10.1029/145gm08, so the approach introduced here is called SVEI. We show examples of the use of SVEI and explain how to use this newly developed Python code that is publicly available in the PmagPy GitHub repository.
Evaluation of the effects of different lightning protection rods on the data quality of C-band weather radars
Cornelius Hald, Maximilian Schaper, Annette Böhm, Michael Frech, Jan Petersen, Bertram Lange, and Benjamin Rohrdantz
Atmos. Meas. Tech., 17, 4695–4707, https://doi.org/10.5194/amt-17-4695-2024, 2024
Weather radars should use lightning protection to be safe from damage, but the rods can reduce the quality of the radar measurements. This study presents three new solutions for lightning protection for weather radars and evaluates their influence on data quality. The results are compared to the current system. All tested ones have very little effect on data, and a new lightning protection system with four rods is recommended for the German Meteorological Service.
Abstract
Monitoring the generation and movement of equatorial plasma bubbles (EPBs) in a large longitude region is crucial important for better understanding their day-to-day variability. Using the newly developed Low lAtitude long Range Ionospheric raDar (LARID) at Dongfang (19.2°N, 108.8°E, dip lat. 13.8°N), China, an extremely long-range experiment for observing EPB irregularities in a range of ±9,600 km to the radar site was first carried out. The results show that EPB irregularities with ranges up to 7,000 and 9,500 km were observed by the east and west beams of LARID, respectively. By incorporating simultaneous observations from GNSS receiver and ionosonde networks, it is demonstrated that the EPBs generated from post-sunset to sunrise over a very wide longitude of ∼140°, from Pacific to Africa could be observed by LARID. The results, for the first time, demonstrate the possibility for tracing global EPBs in real time using a few low latitude over-the-horizon radars.
If you were to slice through it, you would see the Earth is divided into distinct layers. On top is the relatively thin crust where we live. Beneath that is the 2,900 km thick mantle layer. Then, enclosed within the mantle is the innermost metallic core of our planet.
Abstract
Different meteor radars at low latitudes observed abnormally strong westward mesospheric winds around the March Equinox of 2023, that is, during the first phase of the Mesospheric Semiannual Oscillation. This event was the strongest of at least the last decade (2014–2023). The westward winds reached −80 m/s at 82 km of altitude in late March, and decreased with increasing altitude and latitude. A considerable increase in the diurnal tide amplitude was also observed. The Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension constrained to meteorological reanalysis up to ∼50 km does not capture the observed low-latitude behavior. Additionally, these strong mesospheric winds developed during the westerly phase of the Quasi-Biennial Oscillation, in accordance with the filtering mechanism of gravity waves in the stratosphere proposed in previous works. Finally, analysis of SABER temperatures strongly suggests that the breaking of the migrating diurnal tide may be the main driver of these strong winds.
Abstract
Anti-dipolarization fronts (ADFs), characterized by the rapid increase of the negative magnetic field Bz component, are typically formed at the leading edge of the tailward reconnection jets in the Earth's magnetotail. To date, the electron-scale current structures, which govern the energy conversion at ADFs, are still barely understood due to the lack of high-resolution measurements. Here, using Magnetospheric Multiscale mission, we for the first time report a tailward ADF associated with strong field-aligned current (FAC). The FAC appears at the leading part of the ADF and its densities can reach about 200 nA/m2, which is significantly larger than those reported before. Such current is primarily contributed by the electron flow, which also forms electron beam distribution in the anti-parallel direction. Significant energy conversion (E⋅ J, E is electric field and J is current density) is also observed at the ADF, which is mainly contributed by the FAC and the fluctuating electric fields. This study makes essential steps toward understanding the current system and the energy conversion at the ADF in the Earth's magnetotail.
Abstract
Silver is a highly toxic element for marine organisms. However, its controlling factor in marine sediments remains largely unknown, limiting our understanding of its biogeochemical cycling. Based on a sediment core from the Vietnam upwelling area in the South China Sea, it is found that Ag is significantly enriched in sediments of this area (as high as 0.39 μg/g), and it shows a very similar geochemical behavior to Ca and Sr. Our study supports the theory that Ag could be a marine paleo-productivity indicator. Burial of Ag over the past 3,200 years shows an abrupt increase at around 1850 CE, in concordance with the global atmospheric CO2 record. It is hypothesized that elevated CO2 and global warming enhance marine productivity in the Vietnam coastal upwelling area, favoring the burial of Ag. Human-induced global warming thus significantly impacts its biogeochemical cycling.
Abstract
Dry lightning is a prevalent episodic natural ignition source for wildfires, particularly in remote regions where such fires can escalate into uncontrollable events, burning extensive areas. In this study, we aimed to understand the interplay of environmental, fuel, and geographical factors in evaluating the probability of fire initiation following dry lightning strikes in Tasmania, Australia. We integrated dry lightning, active fire records, and gridded data on fire weather, fuel, and topography into a binary classification framework for both fire-initiating and non-fire-causing lightning strikes. Employing statistical and machine learning techniques, we quantified the likelihood of fire initiation due to dry lightning, with the resampled Random Forest model exhibiting notable performance with an ROC-AUC value of 0.98. Our findings highlight how fuel characteristics and moisture content associated with particular vegetation types influence fire initiation and provide an objective approach for identifying susceptible regions of dry lightning ignitions, informing associated fire management responses.
Last year marked Earth's warmest year on record. A new study finds that some of 2023's record warmth, nearly 20%, likely came as a result of reduced sulfur emissions from the shipping industry. Much of this warming is concentrated over the northern hemisphere.
